具有完成时间、飞行距离和资源消耗约束的无人机任务调度

IF 3.2 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Connection Science Pub Date : 2023-11-10 DOI:10.1080/09540091.2023.2281250
Keqin Li
{"title":"具有完成时间、飞行距离和资源消耗约束的无人机任务调度","authors":"Keqin Li","doi":"10.1080/09540091.2023.2281250","DOIUrl":null,"url":null,"abstract":"Unmanned aerial vehicles (UAVs) are widely used in various military and civilian applications. UAV mission scheduling is a key issue in UAV applications and a central topic in UAV research. UAV task scheduling should include several constraints into consideration, such as completion time constraint, flight distance constraint, and resource consumption constraint. Furthermore, UAV task scheduling should be studied within the traditional framework of combinatorial optimisation. In this paper, we consider optimal mission scheduling for heterogeneous UAVs with completion time, flight distance, and resource consumption constraints. The contributions of the paper are summarised as follows. We define two combinatorial optimisation problems, namely, the NFTM (number of finished tasks maximisation) problem and the RFTM (reward of finished tasks maximisation) problem. We construct an algorithmic framework for both NFTM and RFTM problems, so that our heuristic algorithms (four for NFTM and two for RFTM) can be presented in a unified way. We derive upper bounds for optimal solutions, so that our heuristic solutions can be compared with optimal solutions. We experimentally evaluate the performance of our heuristic algorithms. To the best of our knowledge, this is the first paper studying UAV mission scheduling with time, distance, and resource constraints as combinatorial optimisation problems.","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UAV mission scheduling with completion time, flight distance, and resource consumption constraints\",\"authors\":\"Keqin Li\",\"doi\":\"10.1080/09540091.2023.2281250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unmanned aerial vehicles (UAVs) are widely used in various military and civilian applications. UAV mission scheduling is a key issue in UAV applications and a central topic in UAV research. UAV task scheduling should include several constraints into consideration, such as completion time constraint, flight distance constraint, and resource consumption constraint. Furthermore, UAV task scheduling should be studied within the traditional framework of combinatorial optimisation. In this paper, we consider optimal mission scheduling for heterogeneous UAVs with completion time, flight distance, and resource consumption constraints. The contributions of the paper are summarised as follows. We define two combinatorial optimisation problems, namely, the NFTM (number of finished tasks maximisation) problem and the RFTM (reward of finished tasks maximisation) problem. We construct an algorithmic framework for both NFTM and RFTM problems, so that our heuristic algorithms (four for NFTM and two for RFTM) can be presented in a unified way. We derive upper bounds for optimal solutions, so that our heuristic solutions can be compared with optimal solutions. We experimentally evaluate the performance of our heuristic algorithms. To the best of our knowledge, this is the first paper studying UAV mission scheduling with time, distance, and resource constraints as combinatorial optimisation problems.\",\"PeriodicalId\":50629,\"journal\":{\"name\":\"Connection Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Connection Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09540091.2023.2281250\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2023.2281250","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

无人驾驶飞行器(uav)广泛应用于各种军事和民用领域。无人机任务调度是无人机应用中的关键问题,也是无人机研究的中心课题。无人机任务调度需要考虑完成时间约束、飞行距离约束和资源消耗约束等约束条件。此外,无人机任务调度还应在传统的组合优化框架下进行研究。研究了具有完成时间、飞行距离和资源消耗约束的异构无人机任务调度问题。本文的贡献总结如下。我们定义了两个组合优化问题,即NFTM(完成任务数量最大化)问题和RFTM(完成任务奖励最大化)问题。我们为NFTM和RFTM问题构建了一个算法框架,以便我们的启发式算法(NFTM的四个算法和RFTM的两个算法)可以统一地呈现。我们推导了最优解的上界,使我们的启发式解可以与最优解进行比较。我们通过实验评估我们的启发式算法的性能。据我们所知,这是第一篇将时间、距离和资源约束作为组合优化问题研究无人机任务调度的论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
UAV mission scheduling with completion time, flight distance, and resource consumption constraints
Unmanned aerial vehicles (UAVs) are widely used in various military and civilian applications. UAV mission scheduling is a key issue in UAV applications and a central topic in UAV research. UAV task scheduling should include several constraints into consideration, such as completion time constraint, flight distance constraint, and resource consumption constraint. Furthermore, UAV task scheduling should be studied within the traditional framework of combinatorial optimisation. In this paper, we consider optimal mission scheduling for heterogeneous UAVs with completion time, flight distance, and resource consumption constraints. The contributions of the paper are summarised as follows. We define two combinatorial optimisation problems, namely, the NFTM (number of finished tasks maximisation) problem and the RFTM (reward of finished tasks maximisation) problem. We construct an algorithmic framework for both NFTM and RFTM problems, so that our heuristic algorithms (four for NFTM and two for RFTM) can be presented in a unified way. We derive upper bounds for optimal solutions, so that our heuristic solutions can be compared with optimal solutions. We experimentally evaluate the performance of our heuristic algorithms. To the best of our knowledge, this is the first paper studying UAV mission scheduling with time, distance, and resource constraints as combinatorial optimisation problems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Connection Science
Connection Science 工程技术-计算机:理论方法
CiteScore
6.50
自引率
39.60%
发文量
94
审稿时长
3 months
期刊介绍: Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing. A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.
期刊最新文献
Devising single in-out long short-term memory univariate models for predicting the electricity price on the day-ahead markets Parkinson's disease detection and stage classification: quantitative gait evaluation through variational mode decomposition and DCNN architecture A continual learning framework to train robust image recognition models by adversarial training and knowledge distillation Enhancing image data security using the APFB model IPFS-blockchain-based delegation model for internet of medical robotics things telesurgery system
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1